Electronic system and method for dynamically adjusting fan speed

Abstract

Sample noise signals of a fan operating at a predetermined speed in a noiseless environment are detected, and overall ambient noise signals of the fan operating at the predetermined speed in a noisy environment are detected. The sample noise signals and the overall ambient noise signals are then analyzed to obtain a probability distribution of the degree of similarity between the sample noise signals and the overall ambient noise signals, and the speed of the fan is dynamically adjusted based on the size relationship between the probability distribution and a threshold value.

Description

Technical Field

[0001] The present invention relates to an electronic system and method for dynamically adjusting fan speed, and more particularly to an electronic system and method for dynamically adjusting fan speed according to current ambient sound characteristics. Background Art

[0002] In the modern information society, computer systems have become indispensable tools for most people. To prevent component power loss or damage due to overheating, computer systems typically use fans to dissipate heat generated within the device or draw in cool air from outside. Fan speed and static pressure determine the fan's airflow. The noise level of a running fan is roughly proportional to the fifth root of its speed. Faster speeds increase heat dissipation but also produce greater noise.

[0003] In applications in quiet environments, fans usually operate at the lowest speed. Generally speaking, most users can accept fan noise that is more than 3dB lower than the ambient noise. Therefore, previous technologies control the fan speed based on the power of the ambient sound signal received by the microphone: when the overall power is greater than the critical value, the allowable fan noise is higher, so the fan speed is increased to improve heat dissipation efficiency; when the overall power is less than the critical value, the allowable fan noise is lower, so the fan speed is reduced to avoid affecting the user's perception. However, the operating premise of the previous technology assumes that the fan noise signal corresponding to the influence of the microphone is a fixed power. In fact, when the fan is installed in a mobile device, it may move continuously during operation. In different environments, the fan noise signal corresponding to the influence of the microphone will constantly change, especially when close to a wall, causing sound wave reflection.

[0004] Therefore, there is a need for an electronic system and method that can dynamically adjust the fan speed according to the current ambient sound characteristics, thereby taking into account both heat dissipation and noise reduction. Summary of the Invention

[0005] The present invention provides an electronic system for dynamically adjusting fan speed, comprising a fan, a sound receiving device, and a controller. The fan operates according to a fan control signal to provide heat dissipation. The sound receiving device is used to detect a first sample noise signal when the fan operates at a first speed in a silent environment, and to detect the noise generated when the fan operates at the first speed in a noisy environment, to provide a first overall environmental noise signal of the electronic system. The controller is used to provide the fan control signal according to a mode signal, analyze the first sample noise signal and the first overall environmental noise signal to obtain a first probability distribution related to the degree of similarity between the first sample noise signal and the first overall environmental noise signal, and dynamically adjust the fan speed according to the relationship between the first probability distribution and a first critical value.

[0006] The present invention further provides a method for dynamically adjusting fan speed, comprising detecting a first sample noise signal of a fan in an electronic system operating at a first speed in a silent environment; detecting noise generated by the fan operating at the first speed in a noisy environment to provide a first overall ambient noise signal of the electronic system; analyzing the first sample noise signal and the first overall ambient noise signal to determine a first probability distribution related to the degree of similarity between the first sample noise signal and the first overall ambient noise signal; and dynamically adjusting the fan speed based on a relationship between the first probability distribution and a first threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 FIG. 4 is a functional block diagram of an electronic system for dynamically adjusting fan speed according to current ambient sound characteristics in an embodiment of the present invention.

[0008] Figure 2 FIG. 2 is a schematic diagram of an electronic system implementation method according to an embodiment of the present invention.

[0009] Figure 3 This is a flow chart of an electronic system dynamically adjusting the fan speed according to the current ambient sound characteristics in an embodiment of the present invention.

[0010] in:

[0011] 10: Processor;

[0012] 20: fan;

[0013] 30: radio receiver;

[0014] 40: controller;

[0015] 50: memory unit;

[0016] 100: electronic system;

[0017] 310-400: steps;

[0018] S FG : Fan control signal;

[0019] S MODE : Mode signal. DETAILED DESCRIPTION

[0020] Figure 1 FIG2 is a functional block diagram of an electronic system 100 for dynamically adjusting fan speed according to current ambient sound characteristics according to an embodiment of the present invention. The electronic system 100 includes a processor 10 , a fan 20 , a sound receiving device 30 , a controller 40 , and a memory unit 50 .

[0021] The processor 10 may be a central processing unit (CPU) or a graphics processing unit (GPU). It is a key computing engine in the electronic system 100 , responsible for executing instructions and programs required by the operating system, and is also the main source of waste heat in the electronic system 100 .

[0022] The fan 20 may have different structures depending on its type, but they all use a motor to drive the fan blades to rotate, so as to bring cooler air into the chassis and exhaust the hotter air inside, thereby achieving a heat dissipation effect. In the present invention, the fan 20 will be based on a fan control signal S provided by the controller 40. FG To operate, the fan control signal S FG The larger the value, the faster the motor speed of the fan 20, the stronger the heat dissipation effect, but it will also generate greater noise. During the operation of the electronic system 100, the fan 20 is usually the main source of noise. In one embodiment, the fan control signal S FG The signal may be a pulse width modulated (PWM) square wave signal, which adjusts the motor speed of the fan 20 by varying its duty cycle. In one embodiment, the fan 20 may be an axial fan or a centrifugal fan. However, the type and drive method of the fan 20 do not limit the scope of the present invention.

[0023] The sound receiving device 30 is used to capture noise during the operation of the electronic system 100 and output a corresponding noise signal to the controller 40. In one embodiment, the sound receiving device 30 may be a digital micro-electromechanical system (MEMS) microphone, which has high heat resistance, high vibration resistance, and high resistance to radio frequency interference. However, the type of sound receiving device 30 does not limit the scope of the present invention.

[0024] The controller 40 can be configured to generate a mode signal S MODE To control the operation of the processor 10 and the fan 20. The mode signal S MODE The value of determines the operating mode of the fan 20, such as performance mode, optimal mode, and silence mode. In performance mode, the fan 20 runs at a higher speed, which improves the cooling effect but also generates more noise. In optimal mode, the fan 20 speed automatically adjusts based on the temperature of the processor 10. In silence mode, the fan 20 runs at a lower speed, which minimizes noise but also limits the cooling effect.

[0025] Memory unit 50 can be used to store data required for the operation of electronic system 100, as well as data acquired during operation. Memory unit 50 can be a random access memory (RAM), flash memory, or various forms of hard disk. However, the implementation of memory unit 50 does not limit the scope of the present invention.

[0026] Figure 2 FIG. 1 is a schematic diagram of an implementation of the electronic system 100 according to an embodiment of the present invention. Figure 2 In the illustrated embodiment, the electronic system 100 may be a notebook computer, wherein the audio receiving device 30 is disposed on the upper housing and above the screen, while the processor 10, fan 20, controller 40, and memory unit 50 are disposed within the lower housing. However, the implementation of the electronic system 100 does not limit the scope of the present invention.

[0027] Figure 3 This is a flow chart of an electronic system 100 dynamically adjusting the fan speed according to the current ambient sound characteristics according to an embodiment of the present invention, which includes the following steps:

[0028] Step 310: In a silent environment, the sound receiving device 30 detects that the fan 20 rotates at N speeds SP1-SP N Sample noise signal S during operation X1 -S XN .

[0029] Step 320: In a general environment, the controller 40 generates a signal according to the mode signal S MODE To provide fan control signal S FG .

[0030] Step 330: In a normal environment, when the fan 20 is controlled by the fan control signal S FG When operating at the first rotation speed SP1, the sound receiving device 30 detects the overall environmental noise signal S of the electronic system 100. Y1 .

[0031] Step 340: The controller 40 analyzes the sample noise signal S corresponding to the first rotation speed SP1 X1 and the overall ambient noise signal S Y1 , in order to find the relevant sample noise signal S X1 and the overall ambient noise signal S Y1 The probability distribution P of the similarity between XY1 .

[0032] Step 350: The controller 40 calculates the probability distribution P XY1 The rotation speed of the fan 20 is dynamically adjusted according to the relationship between the value of the threshold and a first threshold TH1.

[0033] Step 360: In a normal environment, when the fan 20 is controlled by the fan control signal S FG At nth speed SP n During operation, the sound receiving device 30 detects the overall environmental noise signal S of the electronic system 100. Yn .

[0034] Step 370: The controller 40 analyzes the corresponding n-th speed SP n Sample noise signal S Xn and the overall ambient noise signal S Yn , in order to find the relevant sample noise signal S Xn and the overall ambient noise signal S Yn The probability distribution P of the similarity between XYn .

[0035] Step 380: When the probability distribution P XYn When the overall ambient noise signal S is less than a second threshold value TH2 for more than a predetermined time, Yn Stored in the memory unit 50.

[0036] Step 390 : The controller 40 determines whether the fan 20 has been operating for more than a predetermined period in a normal environment. If yes, the controller 40 executes step 400 ; if no, the controller 40 executes step 320 .

[0037] Step 400: Update the sample noise signal S according to all stored overall environmental noise signals X1 -S XN ; Execute step 320.

[0038] In step 310, the fan 20 is operated at different speeds in a silent environment, and the sound receiving device 30 obtains the N speeds SP1-SP N Sample noise signal S during operation X1 -S XN , where N is an integer greater than 1. The speed of the fan 20 will only affect the narrowband noise frequency. The faster the speed of the fan 20, the smaller the sample noise signal S X1 -S XN The frequency response characteristics of the mid-band noise remain unchanged, but the amplitude increases. Therefore, in a silent environment, when the fan 20 operates at different speeds, the sample noise signals S of the N speeds are obtained. X1 -S XN The characteristic value of can be used as an initial built-in sample. In one embodiment, the anechoic environment can be an anechoic room, an anechoic box, or any experimental environment without a reflective sound field, but the scope of the present invention is not limited thereto.

[0039] In step 320 , when the electronic system 100 operates in a normal environment, the controller 40 will generate a signal according to the mode signal SMODE To provide fan control signal S FG As mentioned above, the mode signal S MODE The value of can determine the operation mode of the fan 20, such as operating in high-performance mode, optimization mode and quiet mode.

[0040] In step 330, when the fan 20 is in a normal environment, the fan 20 is controlled by the fan control signal S FG When operating at the first rotation speed SP1, the sound receiving device 30 detects the overall environmental noise signal S of the electronic system 100. Y1 When the electronic system 100 operates in different environments, the noise signal of the fan 20 corresponding to the effect of the sound receiving device 30 will constantly change, especially when it is close to the wall causing sound wave reflection. Y1 The noise may come from both the operation of the fan 20 and the background environment. Therefore, the controller 40 analyzes the sample noise signal S corresponding to the first rotation speed SP1 in step 340. X1 and the overall ambient noise signal S Y1 , to obtain the sample noise signal S corresponding to the first speed SP1 X1 and the overall ambient noise signal S Y1 The probability distribution P of the similarity between XY1 .

[0041] In one embodiment, the controller 40 compares the sample noise signal S through deep learning. X1 and the overall ambient noise signal S Y1 If the characteristic value difference between the two is the same, the sample noise signal S corresponding to the first speed SP1 X1 and the overall ambient noise signal S Y1 The more similar the eigenvalues ​​are, the more likely the probability distribution P is XY1 Similarly, if the sample noise signal S corresponding to the first speed SP1 X1 and the overall ambient noise signal S Y1 The more different the eigenvalues ​​are, the more likely the probability distribution P is XY1 The smaller the value.

[0042] In step 350, the controller 40 will calculate the probability distribution P XY1 The speed of the fan 20 is dynamically adjusted based on the relationship between the probability distribution P and the first threshold value TH1. XY1 When the value is greater than the first threshold TH1, it means that the overall environmental noise signal S Y1 The noise mainly comes from the operation of the fan 20 (the permissible fan noise is relatively small), so the controller 40 adjusts the fan control signal S FG To reduce the speed of the fan 20; when the probability distribution P XY1When the value is not greater than the first threshold value TH1, it means that the overall environmental noise signal S Y1 Mainly from the background environment (the permissible fan noise is relatively large), so the controller 40 will adjust the fan control signal S FG To increase the rotation speed of the fan 20.

[0043] After long-term use, the noise characteristics generated by the fan 20 during operation may change, causing the sample noise signal S obtained in step 310 to be X1 -S XN Therefore, the present invention updates the sample noise signal S in steps 360-400 according to the operating conditions of the fan 20 during the predetermined period. X1 -S XN .

[0044] In step 360, in a normal environment, when the fan 20 is controlled by the fan control signal S FG At nth speed SP n During operation, the sound receiving device 30 detects the overall environmental noise signal S of the electronic system 100. Yn , wherein n is an integer greater than 1 and not greater than N. In step 370, the controller 40 analyzes the corresponding n-th speed SP n Sample noise signal S Xn and the overall ambient noise signal S Yn , in order to find the relevant sample noise signal S Xn and the overall ambient noise signal S Yn The probability distribution P of the similarity between XYn .

[0045] In one embodiment, the controller 40 compares the sample noise signal S through deep learning. Xn and the overall ambient noise signal S Yn The characteristic value difference between the two, if the corresponding n-th speed SP n Sample noise signal S Xn and the overall ambient noise signal S Yn The more similar the eigenvalues ​​are, the more likely the probability distribution P is XYn Similarly, if the corresponding nth speed SP n Sample noise signal S Xn and the overall ambient noise signal S Yn The more different the eigenvalues ​​are, the more likely the probability distribution P is XYn The smaller the value.

[0046] In step 380, when the controller 40 determines the probability distribution P XYn When the value is not less than the second threshold value TH2, it means that the sample noise signal S obtained in step 310 is X1 -SXN The operating characteristics of the fan 20 can still be accurately reflected. At this time, the corresponding n-th speed SP will not be recorded. n The overall environmental noise signal S Yn When the controller 40 determines the probability distribution P XYn When the value of is less than the second threshold value TH2 for no more than a predetermined time, it indicates that it may be a short-term influence of external noise, and the sample noise signal S obtained in step 310 is X1 -S XN The operating characteristics of the fan 20 can still be accurately reflected. At this time, the corresponding n-th speed SP will not be recorded. n The overall environmental noise signal S Yn When the controller 40 determines the probability distribution P XYn When the value of is less than the second threshold value TH2 for more than a predetermined time, it means that the sample noise signal S obtained in step 310 is X1 -S XN The operating characteristics of the fan 20 can no longer be accurately reflected. At this time, the corresponding n-th speed SP will be recorded. n The overall environmental noise signal S Yn .

[0047] As mentioned above, the speed of the fan 20 will only affect the narrowband noise frequency. The faster the speed of the fan 20, the higher the noise signal S X1 -S XN The frequency response characteristics of the mid-band noise remain unchanged, but the amplitude increases. Therefore, in the present invention, the second threshold value TH2 is much smaller than the first threshold value TH1.

[0048] In the present invention, the first speed SP1 corresponds to the quiet mode of the fan 20, and the nth speed SP n This corresponds to the high performance mode or the optimization mode of the fan 20. That is, the value of the first speed SP1 is less than the nth speed SP n The value.

[0049] In step 390, the controller 40 determines whether the fan 20 has been operating in a normal environment for more than a predetermined period. If the fan 20 has not been operating in a normal environment for more than the predetermined period, steps 360-380 may be executed multiple times, and multiple overall environmental noise signals may be stored. When the fan 20 has been operating in a normal environment for more than the predetermined period, the noise characteristics generated by the fan 20 may change. In this case, the sample noise signal S is updated in step 400 based on all stored overall environmental noise signals. X1 -S XN , so that the updated sample noise signal S X1 -S XN It can accurately reflect the operating characteristics of the fan 20 after it has operated for more than a predetermined period.

[0050] In summary, the present invention utilizes deep learning to determine the probability that the overall ambient noise signal is caused by the fan, and then adjusts the fan speed accordingly. Therefore, the present invention provides an electronic system and method that dynamically adjusts fan speed based on the current ambient sound characteristics, thereby simultaneously addressing environmental changes, heat dissipation, and noise reduction.

[0051] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the claims of the present invention should fall within the scope of the present invention.

Claims

1. An electronic system for dynamically adjusting fan speed, comprising: a fan, configured to operate according to a fan control signal to provide a heat dissipation function; A radio receiving device for: Detecting a first sample noise signal when the fan is operating at a first speed in a silent environment; and detecting noise generated by the fan when operating at the first speed in a noisy environment to provide a first overall environmental noise signal of the electronic system; A controller, used to: providing the fan control signal according to a mode signal; Analyzing the first sample noise signal and the first overall ambient noise signal to obtain a first probability distribution related to the similarity between the first sample noise signal and the first overall ambient noise signal; and The fan speed is dynamically adjusted according to the relationship between the first probability distribution and a first critical value; wherein, When the value of the first probability distribution is determined to be greater than the first threshold, the fan control signal is adjusted to reduce the value of the first speed; and when the value of the first probability distribution is determined to be not greater than the first threshold, the fan control signal is adjusted to increase the value of the first speed.

2. The electronic system according to claim 1, wherein: The radio receiver is also used to: Detecting a second sample noise signal when the fan operates at a second speed in the silent environment; and detecting noise generated by the fan operating at the second speed in the noisy environment to provide a second overall environmental noise signal of the electronic system; The controller is also used to: Analyzing the second sample noise signal and the second overall ambient noise signal to obtain a second probability distribution related to a similarity between the second sample noise signal and the second overall ambient noise signal; When it is determined that the second probability distribution is less than a second threshold value for more than a predetermined time, storing the second overall environmental noise signal; as well as When it is determined that the fan has been operating in the noisy environment for more than a predetermined period, updating the first sample noise signal according to the second overall environmental noise signal; and The second rotational speed is greater than the first rotational speed.

3. The electronic system according to claim 2, wherein: The controller uses deep learning to analyze the first sample noise signal and the first overall environmental noise signal to obtain the first probability distribution, and analyzes the second sample noise signal and the second overall environmental noise signal to obtain the second probability distribution.

4. The electronic system according to claim 2, wherein: The device further comprises a memory unit for storing the first sample noise signal, the first overall environment noise signal, the second sample noise signal, and the second overall environment noise signal.

5. A method for dynamically adjusting fan speed, comprising: Detecting a first sample noise signal of a fan in an electronic system operating at a first speed in a silent environment; detecting noise generated by the fan operating at the first speed in a noisy environment to provide a first overall environmental noise signal of the electronic system; Analyzing the first sample noise signal and the first overall ambient noise signal to obtain a first probability distribution related to the similarity between the first sample noise signal and the first overall ambient noise signal; and The fan speed is dynamically adjusted according to the relationship between the first probability distribution and a first critical value; wherein, When it is determined that the value of the first probability distribution is greater than the first critical value, the value of the first rotational speed is reduced; and when it is determined that the value of the first probability distribution is not greater than the first critical value, the value of the first rotational speed is increased.

6. The method according to claim 5, wherein Also includes: Deep learning is used to analyze the first sample noise signal and the first overall environmental noise signal to obtain the first probability distribution.

7. The method according to claim 5, wherein Also includes: Detecting a second sample noise signal when the fan operates at a second speed in the silent environment; detecting noise generated by the fan operating at the second speed in the noisy environment to provide a second overall environmental noise signal of the electronic system; Analyzing the second sample noise signal and the second overall ambient noise signal to obtain a second probability distribution related to a similarity between the second sample noise signal and the second overall ambient noise signal; When it is determined that the second probability distribution is less than a second threshold value for more than a predetermined time, storing the second overall environmental noise signal; as well as When it is determined that the fan has been operating in the noisy environment for more than a predetermined period, the first sample noise signal is updated according to the second overall environmental noise signal, wherein the second rotation speed is greater than the first rotation speed.

8. The method according to claim 7, wherein Also includes: Deep learning is used to analyze the second sample noise signal and the second overall environmental noise signal to obtain the second probability distribution.

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